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Conference papers
Polar Sine Based Siamese Neural Network for Gesture Recognition
Abstract : Our work focuses on metric learning between gesture sample signatures using Siamese Neural Networks (SNN), which aims at model-ing semantic relations between classes to extract discriminative features. Our contribution is the notion of polar sine which enables a redefini-tion of the angular problem. Our final proposal improves inertial gesture classification in two challenging test scenarios, with respective average classification rates of 0.934 ± 0.011 and 0.776 ± 0.025.
Cited literature [14 references]
https://hal.archives-ouvertes.fr/hal-01369302
Contributor : Stefan Duffner <>
Submitted on : Tuesday, September 20, 2016 - 5:16:46 PM
Last modification on : Monday, February 15, 2021 - 9:34:02 AM
Contributor : Stefan Duffner <>
Submitted on : Tuesday, September 20, 2016 - 5:16:46 PM
Last modification on : Monday, February 15, 2021 - 9:34:02 AM
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icann2016.pdf
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